The Database Group @ University of Toronto LinQuer: Linkage Query Writer
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   Project Description
  Discovering links between different entities in data sources is a challenging task and an attractive research area. Existence of links add value to data sources, enhance data access and information discovery, and allow or enhance many increasingly important data mining tasks. When data sources are not linked, they resemble islands of data (or data silos), where each island maintains only part of the data necessary to satisfy a user's information needs. Penetrating these silos to both understand their contents and understand potential semantic connections is a daunting task. What users and data publishers need is automated support for creating referential links between data that reside in different sources and that are semantically related.  Finding such links often requires the use of approximate matching (to overcome syntactic representational differences and errors) and semantic matching (to find specific semantic relationships).  Furthermore, both types of matching must be tightly integrated to accommodate for the tremendous heterogeneity found in the data that reside in today's information systems.

LinQuer is a system for generating SQL queries for semantic link discovery over relational data. The LinQuer framework consists of
    * LinQL, a language for specification of linkage requirement
    * A web interface and an API for translating LinQL queries to standard SQL queries
    * An interface that assists users in writing LinQL queries.
  • Framework for Semantic Link Discovery Over Relational Data 
    O. Hassanzadeh, A. Kementsietsidis, L. Lim, R. J. Miller and M. Wang.
    Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM 2009)
  • Linkage Query Writer
    O. Hassanzadeh, R. Xin, R. J. Miller, A. Kementsietsidis, L. Lim, and M. Wang.
    Proceedings of the VLDB Endowment VLDB Endowment, Volume 2 Issue 2, August 2009 (Demonstration Track)
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